Credits: The Register
Boffins from Graz University of Technology in Austria have devised an automated system for browser profiling using two new side channel attacks that can help expose information about software and hardware to fingerprint browsers and improve the effectiveness of exploits.
The researchers say their automated browser profiling scheme facilitates browser fingerprinting, overcomes some anti-fingerprinting techniques, and shows that browser privacy extensions “can leak more information than they disguise and can even be semi-automatically circumvented, leading to a false sense of security.”
Browser fingerprinting involves gathering information about an internet user’s browser and associated software and hardware, such as the browser type, the operating system, various network request headers, cookies, extensions, screen resolution and so on.
window object – which can also be probed for information.
The findings have implications for anyone under the impression that online privacy or online anonymity can be assured, but particularly for users of the Tor browser, which has been designed to resist fingerprinting. The research suggests Tor’s effort to make users appear to have the same browser fingerprint, thereby blending into the crowd, may fall short if additional data points are considered.
The upshot is: this technique is not going to immediately unmask you, and it’s by no means perfect, but it could potentially be used to track you around the internet and target you with adverts.
performance.timeOrigin). These become a profile.
The variations identified in this matrix of data reveal environmentally-dependent properties in Chrome, Edge, Firefox and mobile Tor, properties that provide information useful for identification and attack targeting.
The other involves measuring timing differences in the memory allocator to infer the allocated size of a memory region.
And their research shows there are far more of these than are covered in official documentation. This means browser fingerprints have the potential to be far more detailed – have more data points – than they are now. The Mozilla Developer Network documentation for Firefox, for example, covers 2,247 browser properties. The researchers were able to capture 15,709. Though not all of these are usable for fingerprinting and some represent duplicates, they say they found about 10,000 usable properties for all browsers.
Schwarz, Lackner, and Gruss conclude by noting that they hope browser makers will consider their findings as they work to improve browser and privacy extensions.